This invention relates to systems and methods for use in designing oil wells and in controlling the drilling of oil wells.
The design of an oil well requires a number of activities. In a typical example, these are:    1. Design well path—being the path the well will take from the surface to and through the reservoir.    2. Design casing scheme—being the placement, size and material characteristics of the casing cemented in the well.    3. Design drill string—being the design of the drill string, bottom hole assembly and drill bit selection for each section of the well.    4. Torque and drag calculations—being the calculation of static and dynamic frictional drag in the well bore due to the movement of the casing and/or drill string during rotary operations.    5. Drilling fluid design—being the design of the drilling fluid and determination of rheological properties.    6. Hydraulics design—being the design of the drilling fluid, flow rate, flow regime and pressure regime along the drillstring, through the bit and along the annulus.    7. Pressure management—being the management of the pressure in the wellbore and the balance between the wellbore pressure, formation fluid pressure and formation fracture pressure.
Ideally, each of these steps would be optimised against known constraints or conditions, which may include subsequent constraints or conditions arising from the output of later steps in the process. Thus, some degree of iteration between steps is necessary.
Current practice is to complete each step individually using manual data input or data selected from a database. Each step is completed before going onto the next step. Each step is completed when certain satisfying conditions are met. These satisfying conditions might not be the optimum solution either for the step under consideration or in terms of the total well design after all the steps have been completed. Any contradictions between the output from a later step and a former step are resolved by returning to the former step to find an alternative solution that satisfies the desired condition. The end result is a set of conditions that have been satisfied and not an optimum solution. For example, step A is completed and the output meets set criteria. Data from step A is entered along with other data into step B. If the output from step B meets set criteria, both step A and step B are said to be optimised. This, however, is not the case; they can only truly be said to satisfy certain conditions, which is not an optimum. An optimum will be reached when the sets of conditions for both step A and step B are optimised.